Self-calibration of a stereo rig in a planar scene by data combination

We present a very simple and effective method for eliminating the degeneracy inherent in a planar scene, and demonstrate its performance in a useful application - binocular self-calibration. The projective geometry of planar scenes suffers from a two-fold ambiguity: projective structure cannot be recovered from a pair of images of the scene, and transformations in projective 3-space are underconstrained for features lying on a plane. We overcome these problems by combining the feature data from different pairs of images where we know the relationship between the images is identical. In essence this generates images of a non-degenerate scene which can then be processed using standard algorithms. The only constraint is that the binocular head must be able to make repeated identical rotations about its axes. The benefits of this technique are demonstrated by its use in solving the problem of self-calibration. The use of data combination enables standard general scene stereo calibration algorithms to be used